Many high throughput approaches for analyzing genetic processes and variation make use of complex mixtures of oligonucleotides to detect, sort, or manipulate gene products and/or genomic fragments, e.g. Brenner et al, Proc. Natl. Acad. Sci., 97: 1665-1670 (2000); Church et al, Science, 240: 185-188 (1988); Chee et al, Science, 274: 610-614 (1996); Shoemaker et al, Nature Genetics, 14: 450-456 (1996); Hardenbol et al, Nature Biotechnology, 21: 673-678 (2003); Kennedy et al, Nature Biotechnology, 21: 1233-1237 (2003); and the like. Such techniques are starting to be employed to genotype individuals to determine susceptibilities to a variety of conditions, including cancer, adverse drug reactions, responsiveness to targeted therapeutics, and the like, particularly in clinical trial settings. As these complex hybridization-based techniques move out of research laboratories and into medical and diagnostic applications, there will be a critical need to ensure that readouts based on the techniques are robust and valid, e.g. Food and Drug Administration, “Class II special controls guidance document: Instrumentation for clinical multiplex test systems,” Guidance for Industry and FDA Staff (Mar. 10, 2005).
When polymorphisms are closely spaced along a gene or genome, certain polymorphisms, particularly insertions or deletions, at one locus may interfere with the detection of a polymorphism at adjacent loci in hybridization-based assays because of anomalous hybridization and/or interference among probes. This situation makes it difficult to determine whether a lack of signal in a readout is due to the absence of a polymorphism, probe degradation, probe interference, or other problems, e.g. Landi et al, BioTechniques, 35: 816-827 (2003). The difficulty of such determinations is exacerbated when highly complex probes are used that comprise hundreds, or even thousands, of hybridizing components.
Such difficulties may be crucial when hybridization-based assays are used to genotype a large set of xenobiotic metabolizing genes to determine an effective dosage of a drug for a patient. Metabolism of xenobiotic substances, such as drugs, is a chemical process, by which the body structurally modifies foreign compounds to enhance their solubility and facilitate their excretion. This involves two distinct metabolic phases: enzymatic oxidation, reduction, and hydrolysis reactions, which expose or add functional groups to produce polar molecules (Phase I metabolism) and addition of endogenous compounds to the molecules to further increase polarity (Phase II metabolism). The bulk of responsibility for the Phase I reactions rests on the cytochrome P450 (CYP450) superfamily of enzymes. The CYP450 family consists of 60 to 100 different monoxygenases that catalyze the oxidative metabolism of lipophilic chemicals. These, together with several members of different families of transport proteins, play a crucial role in the disposition and elimination of a diverse array of therapeutic drugs and other xenobiotics. It is now well established that significant inter-individual variability exists in patient drug disposition and response. Much of the observed heterogeneity is thought to be due to the underlying genetic variation in the human population. Individual differences at a single nucleotide of DNA, otherwise known as single nucleotide polymorphisms (SNPs), are the most abundant source of genetic variation in humans. Many SNPs with potential for altering the activity of proteins involved in drug metabolism, such as the CYP450s have been found, e.g. Daly, Fundamental & Clinical Pharmacology, 17: 27-41 (2003). Phenotypes resulting from these genetic changes can markedly influence a drugs pharmacokinetics or change its efficacy and/or toxicity profile. Several examples exist where subjects carrying certain alleles suffer from a lack of drug efficacy, due to ultrarapid metabolism (UM) or, alternatively, adverse effects from the drug treatment due to impaired drug clearance by poor metabolism (PM). In current clinical practice, the suitability of a drug for a given individual is determined by trial and error. This practice places a significant burden on healthcare systems and costs. Having an accurate genetic profile of a patient's drug metabolizing genes would help ensure that the patient receives the most effective treatment, while avoiding inadvertent adverse drug reactions in poor metabolizers.
In view of this, it would be highly desirable to have available multiplexed hybridization-based assays that could accommodate interfering polymorphisms and methods and compositions that would allow one to factor out specific causes for signal loss or variance in such assays. Such assays would be especially useful in the field of medicine and drug development, where information such assays are being increasingly used in decisions about patients and products.